Countering Terrorism: Digital Policing of Open Source Intelligence and Social Media Using Artificial Intelligence

Klingberg, Sarah

doi:10.1007/978-3-031-06709-9_6

Cited by 3 publications

(2 citation statements)

References 11 publications

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“…The potential of AI in OSINT extends beyond cybersecurity, as shown by (Arroyo et al, 2023), who develop AI-supported tools for debunking scientific misinformation. This emphasis on AI's role in combating misinformation is echoed by (Song et al, 2023), who addresses the creation of fake cyber threat intelligence, indicating the dual-use nature of AI in OSINT, a concern also raised by (Klingberg, 2022;Ranaldi et al, 2022;Riebe, 2023) explore AI's application in law enforcement, particularly in monitoring Dark Web Marketplaces and digital policing for counter-terrorism, respectively. Their findings resonate with (Watters, 2023), who outlines the intersection of AI, digital forensics, and OSINT in cyber counterintelligence, emphasizing the growing importance of AI in various aspects of law enforcement and intelligence gathering.…”

Section: Jan čErnýmentioning

confidence: 99%

Implications of Large Language Models for OSINT: Assessing the Impact on Information Acquisition and Analyst Expertise in Prompt Engineering

Černý

2024

eccws

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This paper explores the potential use of large language models (LLMs) in Open Source Intelligence (OSINT), with a focus on integrating information acquisition and the increasing importance of prompt engineering for analysts. The research includes a comprehensive literature review, which highlights the widespread use of AI in OSINT and the related challenges, such as data validity and ethical concerns. The study emphasizes the significance of prompt engineering as a crucial skill that demands a profound comprehension of LLMs to generate validated intelligence. A model of the OSINT lifecycle that incorporates LLMs is proposed. The paper further discusses updated training in critical thinking, search techniques, and prompt engineering for intelligence professionals. The findings indicate a noteworthy shift in OSINT procedures, highlighting the importance of continuous research and education to fully utilize AI in intelligence gathering.

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Section: Jan čErnýmentioning

confidence: 99%

Implications of Large Language Models for OSINT: Assessing the Impact on Information Acquisition and Analyst Expertise in Prompt Engineering

Černý

2024

eccws

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“…(Kilger & Choo, 2022). As a result, Law Enforcement Officers (LEOs) and other end-users may be deterred from using these technologies (Klingberg, 2022).…”

Section: Introductionmentioning

confidence: 99%

Enhancing Training and Technology Adoption in Terrorism Financing Investigations Through Gamification

Zola,

Segurola,

King

et al. 2024

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The purpose of this publication is to present the methodology followed in the European project Anti-FinTer for training Law Enforcement Agencies (LEAs) and Financial Investigation Units (FIUs) in using emergent technologies to reveal financing activities of terrorism. The study presents, compares, and discusses the results gathered from three Capture-the-Flag events which involved LEAs and FIU officers. Designing curricula and training programs for improving terrorist financing investigations is challenging due to this domain's intricate and rapidly evolving nature and the multi-disciplinary knowledge needed. Furthermore, new tools based on novel paradigms, such as Artificial Intelligence and Big Data, are involved in terrorist financing investigations. However, they are too often unnecessarily complex and hard to use. These characteristics often limit law enforcement and end-users' engagement level and expertise in these technologies. For this reason, in this work, we describe an approach using gamification techniques to enhance technology and knowledge transfer for terrorist financing investigations. In fact, designing and implementing realistic and interactive challenges makes it possible to speed up the learning process, increase officers' expertise in using new technologies and improve their readiness. At the same time, this approach allows technical partners to gather end-user needs and facilitate development/validation cycles. This methodology has been validated in three pilots: one held in Madrid in 2022, a second in The Hague in 2023 and a final one in Vienna in 2023. In these pilots, law enforcement personnel were challenged in addressing tasks related to fighting financing terrorism activities through the dark Dark Web, crypto-assets or new payment systems. Results showed an increasing engagement, motivation, and knowledge in the participants.

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Enhancing law enforcement training: A gamified approach to detecting terrorism financing

Zola,

Segurola,

King

et al. 2024

International Journal of Police Science & Management

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Tools for fighting cyber-criminal activities using new technologies are promoted and deployed every day. However, too often, they are unnecessarily complex and hard to use, requiring deep domain and technical knowledge. These characteristics often limit the engagement of law enforcement and end-users in these technologies, which despite their potential, remain misunderstood. For this reason, in this study, we describe our experience in combining learning and training methods and the potential benefits of gamification to enhance technology transfer and increase adult learning. In this case, participants are experienced practitioners in professions/industries that are exposed to terrorism financing (such as law enforcement officers, financial investigation officers, private investigators). We define training activities on different levels for increasing the exchange of information about new trends and criminal modus operandi among and within law enforcement agencies, intensifying cross-border cooperation and supporting efforts to combat and prevent terrorism-funding activities. A game (hackathon) is designed to address realistic challenges related to the darknet, crypto-assets, new payment systems and dark web marketplaces that could be used for terrorist activities. The entire methodology was evaluated using quizzes, contest results and engagement metrics. In particular, training events show that ∼60% of participants complete the 11-week training course, whereas the hackathon results, gathered in two pilot studies (Madrid and The Hague), show increasing expertise among participants (progression in the points achieved on average). At the same time, more than 70% of participants positively evaluate use of the gamification approach, and more than 85% consider the implemented use cases suitable for their investigations. These outcomes are further discussed to detect the introduced approach's benefits and limitations and improve future events.

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Countering Terrorism: Digital Policing of Open Source Intelligence and Social Media Using Artificial Intelligence

Cited by 3 publications

References 11 publications

Implications of Large Language Models for OSINT: Assessing the Impact on Information Acquisition and Analyst Expertise in Prompt Engineering

Implications of Large Language Models for OSINT: Assessing the Impact on Information Acquisition and Analyst Expertise in Prompt Engineering

Enhancing Training and Technology Adoption in Terrorism Financing Investigations Through Gamification

Enhancing law enforcement training: A gamified approach to detecting terrorism financing

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